Gaussian mixture models as flux prediction method for central receivers
Author(s) -
Annemarie Grobler,
Paul Gauché,
W.J. Smit
Publication year - 2016
Publication title -
aip conference proceedings
Language(s) - English
Resource type - Conference proceedings
eISSN - 1551-7616
pISSN - 0094-243X
DOI - 10.1063/1.4949248
Subject(s) - flux (metallurgy) , heliostat , gaussian , ray tracing (physics) , tracing , gaussian network model , gaussian process , computer science , optics , physics , engineering , materials science , quantum mechanics , electrical engineering , metallurgy , solar energy , operating system
Flux prediction methods are crucial to the design and operation of central receiver systems. Current methods such as the circular and elliptical (bivariate) Gaussian prediction methods are often used in field layout design and aiming strategies. For experimental or small central receiver systems, the flux profile of a single heliostat often deviates significantly from the circular and elliptical Gaussian models. Therefore a novel method of flux prediction was developed by incorporating the fitting of Gaussian mixture models onto flux profiles produced by flux measurement or ray tracing. A method was also developed to predict the Gaussian mixture model parameters of a single heliostat for a given time using image processing. Recording the predicted parameters in a database ensures that more accurate predictions are made in a shorter time frame.
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